src/Gargantext/Prelude.hs

   1 {-|
   2 Module      : Gargantext.Prelude
   3 Description :
   4 Copyright   : (c) CNRS, 2017-Present
   5 License     : AGPL + CECILL v3
   6 Maintainer  : team@gargantext.org
   7 Stability   : experimental
   8 Portability : POSIX
   9
  10 Here is a longer description of this module, containing some
  11 commentary with @some markup@.
  12 -}
  13
  14 {-# OPTIONS_GHC -fno-warn-name-shadowing #-}
  15 {-# OPTIONS_GHC -fno-warn-type-defaults  #-}
  16
  17 {-# LANGUAGE     NoImplicitPrelude       #-}
  18
  19 module Gargantext.Prelude
  20   ( module Gargantext.Prelude
  21   , module Protolude
  22   , headMay
  23   , module Text.Show
  24   , module Text.Read
  25   , cs
  26   , module Data.Maybe
  27   )
  28   where
  29
  30 import Data.Maybe (isJust, fromJust, maybe)
  31 import Protolude ( Bool(True, False), Int, Double, Integer
  32                  , Fractional, Num, Maybe(Just,Nothing)
  33                  , Floating, Char, IO
  34                  , pure, (<*>), (<$>), panic
  35                  , head, flip
  36                  , Ord, Integral, Foldable, RealFrac, Monad, filter
  37                  , reverse, map, zip, drop, take, zipWith
  38                  , sum, fromIntegral, length, fmap, foldl, foldl'
  39                  , takeWhile, sqrt, undefined, identity
  40                  , abs, min, max, maximum, minimum, return, snd, truncate
  41                  , (+), (*), (/), (-), (.), ($), (**), (^), (<), (>), log
  42                  , Eq, (==), (>=), (<=), (<>), (/=)
  43                  , (&&), (||), not
  44                  , fst, snd, toS
  45                  , elem, die, mod, div, const, either
  46                  , curry, uncurry
  47                  , otherwise, when
  48                  )
  49
  50 -- TODO import functions optimized in Utils.Count
  51 -- import Protolude hiding (head, last, all, any, sum, product, length)
  52 -- import Gargantext.Utils.Count
  53 import qualified Data.List     as L hiding (head, sum)
  54 import qualified Control.Monad as M
  55
  56 import Data.Map (Map)
  57 import qualified Data.Map as M
  58
  59 import Data.Map.Strict (insertWith)
  60 import qualified Data.Vector as V
  61 import Safe (headMay)
  62 import Text.Show (Show(), show)
  63 import Text.Read (Read())
  64 import Data.String.Conversions (cs)
  65
  66 --pf :: (a -> Bool) -> [a] -> [a]
  67 --pf = filter
  68
  69 pr :: [a] -> [a]
  70 pr = reverse
  71
  72 --pm :: (a -> b) -> [a] -> [b]
  73 --pm = map
  74
  75 map2 :: (t -> b) -> [[t]] -> [[b]]
  76 map2 fun = map (map fun)
  77
  78 -- Exponential Average
  79 eavg :: [Double] -> Double
  80 eavg (x:xs) = a*x + (1-a)*(eavg xs)
  81   where a = 0.70
  82 eavg [] = 0
  83
  84 -- Simple Average
  85 mean :: Fractional a => [a] -> a
  86 mean xs = if L.null xs then 0.0
  87                        else sum xs / fromIntegral (length xs)
  88
  89 sumMaybe :: Num a => [Maybe a] -> Maybe a
  90 sumMaybe = fmap sum . M.sequence
  91
  92 variance :: Floating a => [a] -> a
  93 variance xs = mean $ map (\x -> (x - m) ** 2) xs where
  94     m = mean xs
  95
  96 deviation :: [Double] -> Double
  97 deviation = sqrt . variance
  98
  99 movingAverage :: Fractional b => Int -> [b] -> [b]
 100 movingAverage steps xs = map mean $ chunkAlong steps 1 xs
 101
 102 ma :: [Double] -> [Double]
 103 ma = movingAverage 3
 104
 105
 106 -- | Function to split a range into chunks
 107 chunkAlong :: Int -> Int -> [a] -> [[a]]
 108 chunkAlong a b l = only (while  dropAlong)
 109     where
 110         only      = map (take a)
 111         while     = takeWhile  (\x -> length x >= a)
 112         dropAlong = L.scanl (\x _y -> drop b x) l ([1..] :: [Integer])
 113
 114 -- | Optimized version (Vector)
 115 chunkAlong' :: Int -> Int -> V.Vector a -> V.Vector (V.Vector a)
 116 chunkAlong' a b l = only (while  dropAlong)
 117     where
 118         only      = V.map (V.take a)
 119         while     = V.takeWhile  (\x -> V.length x >= a)
 120         dropAlong = V.scanl (\x _y -> V.drop b x) l (V.fromList [1..])
 121
 122 -- | TODO Inverse of chunk ? unchunkAlong ?
 123 unchunkAlong :: Int -> Int -> [[a]] -> [a]
 124 unchunkAlong = undefined
 125
 126
 127 -- splitAlong [2,3,4] ("helloworld" :: [Char]) == ["he", "llo", "worl", "d"]
 128 splitAlong :: [Int] -> [Char] -> [[Char]]
 129 splitAlong _ [] = [] -- No list? done
 130 splitAlong [] xs = [xs] -- No place to split at? Return the remainder
 131 splitAlong (x:xs) ys = take x ys : splitAlong xs (drop x ys) -- take until our split spot, recurse with next split spot and list remainder
 132
 133 takeWhileM :: (Monad m) => (a -> Bool) -> [m a] -> m [a]
 134 takeWhileM _ [] = return []
 135 takeWhileM p (a:as) = do
 136     v <- a
 137     if p v
 138         then do
 139             vs <- takeWhileM p as
 140             return (v:vs)
 141         else return []
 142
 143 -- SUMS
 144 -- To select the right algorithme according to the type:
 145 -- https://github.com/mikeizbicki/ifcxt
 146
 147 sumSimple :: Num a => [a] -> a
 148 sumSimple = L.foldl' (+) 0
 149
 150 -- | https://en.wikipedia.org/wiki/Kahan_summation_algorithm
 151 sumKahan :: Num a => [a] -> a
 152 sumKahan = snd . L.foldl' go (0,0)
 153     where
 154         go (c,t) i = ((t'-t)-y,t')
 155             where
 156                 y  = i-c
 157                 t' = t+y
 158
 159 -- | compute part of the dict
 160 count2map :: (Ord k, Foldable t) => t k -> Map k Double
 161 count2map xs = M.map (/ (fromIntegral (length xs))) (count2map' xs)
 162
 163 -- | insert in a dict
 164 count2map' :: (Ord k, Foldable t) => t k -> Map k Double
 165 count2map' xs = L.foldl' (\x y -> insertWith (+) y 1 x) M.empty xs
 166
 167
 168 trunc :: (RealFrac a, Integral c, Integral b) => b -> a -> c
 169 trunc n = truncate . (* 10^n)
 170
 171 trunc' :: Int -> Double -> Double
 172 trunc' n x = fromIntegral $ truncate $ (x * 10^n)
 173
 174
 175 bool2int :: Num a => Bool -> a
 176 bool2int b = case b of
 177                   True  -> 1
 178                   False -> 0
 179
 180 bool2double :: Bool -> Double
 181 bool2double bool = case bool of
 182                   True  -> 1.0
 183                   False -> 0.0
 184
 185
 186
 187 -- Normalizing && scaling data
 188 scale :: [Double] -> [Double]
 189 scale = scaleMinMax
 190
 191 scaleMinMax :: [Double] -> [Double]
 192 scaleMinMax xs = map (\x -> (x - mi / (ma - mi + 1) )) xs'
 193     where
 194         ma  = maximum xs'
 195         mi  = minimum xs'
 196         xs' = map abs xs
 197
 198 scaleNormalize :: [Double] -> [Double]
 199 scaleNormalize xs = map (\x -> (x - v / (m + 1))) xs'
 200     where
 201         v = variance xs'
 202         m = mean     xs'
 203         xs' = map abs xs
 204
 205
 206
 207 normalize :: [Double] -> [Double]
 208 normalize as = normalizeWith identity as
 209
 210 normalizeWith :: Fractional b => (a -> b) -> [a] -> [b]
 211 normalizeWith extract bs = map (\x -> x/(sum bs')) bs'
 212     where
 213         bs' = map extract bs
 214
 215 -- Zip functions to add
 216 zipFst :: ([b] -> [a]) -> [b] -> [(a, b)]
 217 zipFst  f xs = zip (f xs) xs
 218
 219 zipSnd :: ([a] -> [b]) -> [a] -> [(a, b)]
 220 zipSnd f xs = zip xs (f xs)
 221
 222 -- Just
 223 unMaybe :: [Maybe a] -> [a]
 224 unMaybe = map fromJust . L.filter isJust
 225